Global discourse around the future of work tends to focus on office jobs, white-collar automation, and corporate productivity. What is often left out of the conversation is that for the majority of people in the Global South, work is seldom formal.
Across sub-Saharan Africa, South Asia, and much of Latin America, informal work remains the dominant form of employment. In some regions, it represents over 80% of total labour – domestic workers, street vendors, market traders, masons, etc – whose jobs may be un-contracted but are critically important to the economy. According to WIEGO, and the ILO, around 61% of the world’s workers are informally employed – representing 2 billion people.
Imagining the future of work without considering informal workers would be a strategic oversight.
Redesigning informal work
Historically, development frameworks have treated informal work as an indicator of underdevelopment – with the expectation that work should be formalised and absorbed into regulated labour markets. But this assumption is outdated; informality is not shrinking, it’s evolving.
Workers in informal systems are increasingly digital, mobile, and responsive to market trends. Many workers use WhatsApp or Telegram to secure clients, coordinate with co-workers, or advertise services. They are building digital reputations without needing a CV and acquiring skills outside formal institutions.
Rather than eliminate informality, we need to design systems that accommodate it. AI tools offer promising solutions for achieving this.
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Decent work deficits can be brutal for those who rely on informal work to live and feed their families. That’s almost 60% of employed people in the world today – or two billion people.
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— Gilbert F. Houngbo, Director-General, ILO.
AI offers visibility and dignity
One of the central challenges in the informal economy is lack of visibility. Many workers operate outside the reach of national statistics, effective labour protection, or digital verification systems. They are often multilingual, multi-skilled, and mobile, yet poorly documented. AI can help change that.
Voice-based AI tools, powered by natural language processing, can allow workers to navigate platforms in local dialects they understand better. Computer vision can verify craftsmanship through image recognition, enabling workers to build portable portfolios. Machine learning algorithms can match workers to tasks based on availability, proximity, and peer ratings.
In cities like Accra or Ahmedabad, where labour markets are dense but disorganised, AI could help workers and employers find each other more efficiently and equitably. A construction worker could be matched to a project based on past performance, verified by client reviews. A nanny could be rated on punctuality and reliability across multiple employers, creating a verifiable work history.
This kind of system does not formalise workers in the traditional sense, it recognises their economic participation in a way that gives them control, continuity, and credibility.
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Building digital marketplaces
Beyond individual empowerment, AI also offers possibilities at the regional level. Across Africa, the African Continental Free Trade Area aspires to facilitate labour mobility and economic cooperation. But for informal workers it still represents major barriers.
AI-backed platforms could help harmonise job classifications, standardise skills recognition, and translate job descriptions into multiple languages. Predictive analytics could also help governments track labour trends, anticipate informal migration flows, or forecast demand for certain skills in border regions.
In South Asia and Latin America, where similar dynamics exist, AI could enable portable digital identities that allow informal workers to carry their reputations and certifications across regions. These tools can help unlock the full potential of regional integration by making mobility safer, smarter, and more inclusive.
A future shaped by AI
Around the world, we already see glimpses of this transformation. A street vendor in Nairobi uses mobile payments to track daily income. A tailor in Accra gets custom orders via voice notes. A cleaner in Manila negotiates pay through an AI-driven chatbot. These are not one-off cases; they are early signals of what a reimagined labour ecosystem could become.
With the rise of magnetic and generative AI technologies, these trends are set to accelerate. In the near future, we could see informal workers discover jobs through hyper-localised recommendation engines that respond to real-time demand spikes. Think of a plumber in Dar es Salaam being alerted to multiple urgent service needs in their vicinity, filtered by urgency, client rating, and price. AI could help a day labourer in Kampala translate their work history into a verified digital portfolio simply by scanning pictures of previous projects and combining those with AI-generated summaries in multiple languages.
Job-matching platforms could soon feature intelligent avatars that serve as negotiators, translators, and advisors, ensuring that a domestic worker in Lusaka is not only visible to new clients but also equipped to advocate for fairer wages and safer conditions in real time. A mason in Abidjan could have their calendar, transportation routes, and payments managed completely by a voice assistant.
As these systems evolve, we may witness a shift from gig work to platformed labour as strategy – where blue-collar workers operate with the same data-driven advantage once reserved for large enterprises. But to get there, these technologies must be made accessible, equitable, and governed with care. That means building platforms that speak local languages, integrate with informal financial tools, and prioritise worker ownership of data and reputation. AI, if designed to serve them, could become the connective tissue that binds opportunity to agency, across villages, cities, and borders.
The potential for agentic AI to transform industries across the Global South is widely recognized. Yet, unlocking this potential will depend on more than just the technology itself. As highlighted in Modern Diplomacy, realising these benefits requires a “holistic approach” – one that brings together governments, industries, and international partners to make reskilling a top priority. With the right “strategic incentives,” efforts to bridge skill gaps and promote inclusivity can help ensure that AI-driven progress translates into sustainable and equitable economic growth for all.
Two billion people may one day soon come to be connected in services, by AI platforms built just for them.
Weforum